4.7 Article

Mapping soil Pb stocks and availability in mainland France combining regression trees with robust geostatistics

期刊

GEODERMA
卷 170, 期 -, 页码 359-368

出版社

ELSEVIER
DOI: 10.1016/j.geoderma.2011.11.014

关键词

Soil Pb; Availability; Diffuse contamination mapping; Regression tree; Robust geostatistics

资金

  1. French Agency for Environment and Energy Management (ADEME) [0975C0013]
  2. French Group of Scientific Interest in Soil (GIS Sol)
  3. Ministry for Ecology, Sustainable Development, Transports and Housing (MEDDTL)
  4. Ministry for Agriculture, Food, Fisheries and Land planning (MAAPRAT)
  5. ADEME
  6. Institute of Research for Development (IRD)
  7. National Forest Inventory (IFN)
  8. National Institute for Agronomic Research (INRA)
  9. Biotechnology and Biological Sciences Research Council
  10. BBSRC [BBS/E/C/00004943] Funding Source: UKRI
  11. Biotechnology and Biological Sciences Research Council [BBS/E/C/00004943] Funding Source: researchfish

向作者/读者索取更多资源

Maps of lead (Pb) stocks in soils and estimates of its availability are needed to assess risks of contamination. Stocks in soils of total and ethylenediamine tetraacetic acid (EDTA) extractable Pb, as well as Pb availability, assessed by EDTA/total Pb ratio, were measured and calculated to a depth of 30 cm with the French soil monitoring network at sites defined by a regular 16 x 16 km grid. Setting aside punctual anomalies by winsorizing, these properties were mapped using linear mixed models (LMM). LMMs combined conditional partitioning trees upon 5 predictors (pH, texture, parent material, land use, population density) with robust geostatistics to avoid distortion due to outlying values. Rather than selecting the fixed effects according to expert-knowledge, regression trees were used to account for explanatory variables in a single classification. This original method stressed both the necessity for a geostatistical component to complement regression tree models when spatial correlation is evident, and the usefulness of these trees to interpret maps. Pb stocks varied widely with peak concentrations and availability in densely populated areas. Lithology, texture and forestation also affected total Pb stocks. With regards to availability, forestation and pH appeared as key factors. (C) 2011 Elsevier B.V. All rights reserved.

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